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Rough seas ahead for "in-house" data centers
1. Rough seas ahead for “in-
house” data centers
Jonathan Koomey, Ph.D.
http://www.koomey.com
Samsung CIO Forum
San Jose, CA
November 1, 2012
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Jonathan
G.
Koomey
2012
2. What the NY Times didn’t say…
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Koomey
2012
3. Two common ways to use the
word “cloud”
• “The cloud”
• “Cloud computing”*
*this is the way I mainly use the term
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Koomey
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4. Data centers are where the
world of bits meets the world
of atoms
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Koomey
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9. Example: Servers (via Intel)
• Usage Driven
• Variable Utilization
• Proportional Energy Use
• Optimized Efficiency
• Technology Scope:
• CPU and Memory
• Power Delivery, Fans, etc.
• Instrumentation
Approaching “Ideal” Server Behavior
Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark* and MobileMark*, are measured using specific
computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you
in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. Configurations: Dual Socket Server. For full configuration information, please see
backup. For more information go to http://www.intel.com/performance
Xeon™
5160
Xeon™
E5-‐2660
2012
2006
Data from spec.org
Source:
Winston
Saunders,
Intel
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Jonathan
G.
Koomey
2012
10. Data center costs are strongly
affected by IT power use,
particularly server power
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Koomey
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11. Annualized data center costs
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Source:
Koomey
et
al.
2009a
x
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Jonathan
G.
Koomey
2012
12. Low power DRAM and SSDs are
worth more than you think
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Picture
courtesy
of
Samsung
Electronics
Co.
Ltd
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Jonathan
G.
Koomey
2012
13. What’s 1 W of IT savings worth?
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Infrastructure
capital
savings
apply
to
new
construcNon
or
exisNng
faciliNes
that
are
power/cooling
constrained.
Those
savings
total
$8.6M/MW
for
cloud
faciliNes
and
$15M/MW
for
others,
from
UpNme
insNtute.
PUE
=
1.1,
1.5,
and
1.8
for
Cloud,
New,
and
ExisNng
data
centers,
respecNvely.
Electricity
price
=$0.039/kWh
for
cloud
faciliNes
and
$0.066/kWh
for
new/exisNng
data
centers.
All
costs
in
2012
dollars.
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Jonathan
G.
Koomey
2012
14. In spite of our historical progress,
there’s still great potential for
improving the energy
efficiency of data centers
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Jonathan
G.
Koomey
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16. Improving the energy efficiency of
data centers is as much about
people and institutions as it is
about technology
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Jonathan
G.
Koomey
2012
17. Why asset management is key
Slide
courtesy
of
Winston
Saunders,
Intel
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G.
Koomey
2012
18. Lesson 1:
Big potential for efficiency
improvements, especially in
“in-house” data centers
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Jonathan
G.
Koomey
2012
19. Lesson 2:
Fixing misplaced incentives
is the most important step
toward realizing this potential
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Jonathan
G.
Koomey
2012
20. Now on to cloud
computing…
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Jonathan
G.
Koomey
2012
21. For users, cloud computing
offers infinitely scalable
computing on demand
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G.
Koomey
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22. So why should cloud users
care about power use?
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Koomey
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23. Power use strongly affects
costs for “in-house” IT
services (the alternative to
relying on the cloud) AND
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Koomey
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24. Cloud computing suppliers
have at least four big
advantages on power and
costs over
“in-house” IT
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Koomey
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25. 1) Diversity: spread loads
over many users,
improving hardware
utilization
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G.
Koomey
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26. 2) Economies of scale:
implementing technical +
organizational changes is
cheaper and easier than for
small IT shops
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G.
Koomey
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27. 3) Flexibility: management
of virtual servers easier and
cheaper than physical
servers
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G.
Koomey
2012
28. 4) Easier for users to shift
to cloud providers than to
fix the institutional
problems in their internal IT
organizations
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G.
Koomey
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29. My claim:
Powerful economic trends
(driven by these energy
advantages) will push users
more and more
towards cloud computing
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G.
Koomey
2012
31. Big picture: Often better to
move bits than atoms
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Source:
Weber
et
al.
2010
Physical
CDs
Digital
downloads
CO2
emissions
for
downloads
and
physical
CDs
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Jonathan
G.
Koomey
2012
32. General conclusions
• Data centers responsible for about 1.3% of the
world’s electricity use in 2010 (2% for US)
• Absolute electricity use has been growing fast
but growth slowed 2005 to 2010
• Delivery of IT services growing faster than
electricity use (so electricity productivity is up!)
• The indirect productivity benefits of IT are likely
to be more important than direct electricity use.
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G.
Koomey
2012
33. Lessons for “in-house” IT
• IT system and component efficiency (like from low-power
SSDs and DRAM) matter
• “In-house” data centers facing challenges because of
– poor measurement and verification processes
– misplaced incentives
– competition from cloud and other providers
– pressure from the “C-level”
• IT becoming, less general purpose, more custom designed,
and closer to tasks (more mobile)
• CIOs moving from “keepers of systems” to “brokers of
information services”. Get ready!
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G.
Koomey
2012
34. Sign up!: Uptime Server Roundup
• Find and retire comatose servers
• Enroll at http://www.uptimeinstitute.com/
server-roundup
• Submission deadline for this year’s contest:
March 1, 2013
• Submitted results can be anonymous
• Last time participants retired 20,000 servers
and eliminated 5 MW of IT load
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Koomey
2012
35. Key web sites
• EPA on data centers + 2007 Report to Congress
http://www.energystar.gov/datacenters
• LBNL on data centers: http://hightech.lbl.gov/
datacenters.html
• The Green Grid: http://www.thegreengrid.org/
• The Uptime Institute: http://www.uptimeinstitute.org
• SPEC power: http://www.spec.org/power_ssj2008/
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Koomey
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36. References
• Baliga, Jayant, Robert W. A. Ayre, Kerry Hinton, and Rodney S. Tucker. 2010. "Green Cloud
Computing: Balancing Energy in Processing, Storage and Transport." In Press at the
Proceedings of the IEEE. <http://people.eng.unimelb.edu.au/rtucker/publications/files/
Baliga_Ayre_Hinton_Tucker_JRLStrTrans.pdf>
• Barroso, Luzi André, and Urs Hölzle. 2007. "The Case for Energy-Proportional Computing."
IEEE Computer. vol. 40, no. 12. December. pp. 33-37. [http://www.barroso.org/]
• Hilbert, Martin, and Priscila López. 2011. "The World's Technological Capacity to Store,
Communicate, and Compute Information." Science. vol. 332, no. 6025. April 1. pp. 60-65.
• Koomey, Jonathan. 2007a. Estimating regional power consumption by servers: A technical
note. Oakland, CA: Analytics Press. December 5. <http://www.amd.com/koomey>
• Koomey, Jonathan. 2007b. Estimating total power consumption by servers in the U.S. and
the world. Oakland, CA: Analytics Press. February 15. <http://enterprise.amd.com/us-en/
AMD-Business/Technology-Home/Power-Management.aspx>
• Koomey, Jonathan, Kenneth G. Brill, W. Pitt Turner, John R. Stanley, and Bruce Taylor.
2007. A simple model for determining true total cost of ownership for data centers. Santa
Fe, NM: The Uptime Institute. September. <http://www.uptimeinstitute.org/>
• Koomey, Jonathan. 2008. "Worldwide electricity used in data centers." Environmental
Research Letters. vol. 3, no. 034008. September 23. <http://stacks.iop.org/
1748-9326/3/034008>.
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G.
Koomey
2012
37. References (continued)
• Koomey, Jonathan G., Christian Belady, Michael Patterson, Anthony Santos, and Klaus-Dieter
Lange. 2009a. Assessing trends over time in performance, costs, and energy use for servers.
Oakland, CA: Analytics Press. August 17. <http://www.intel.com/pressroom/kits/ecotech>
• Koomey, Jonathan. 2011. Growth in data center electricity use 2005 to 2010. Oakland, CA:
Analytics Press. August 1. <http://www.analyticspress.com/datacenters.html>
• Koomey, Jonathan G., Stephen Berard, Marla Sanchez, and Henry Wong. 2011. "Implications of
Historical Trends in The Electrical Efficiency of Computing." IEEE Annals of the History of
Computing. vol. 33, no. 3. July-September. pp. 2-10. <https://files.me.com/jgkoomey/u0zi7l>
• Masanet, Eric R., Richard E. Brown, Arman Shehabi, Jonathan G. Koomey, and Bruce Nordman.
2011. "Estimating the Energy Use and Efficiency Potential of U.S. Data Centers." Proceedings of
the IEEE. vol. 99, no. 8. August.
• Stanley, John, and Jonathan Koomey. 2009. The Science of Measurement: Improving Data Center
Performance with Continuous Monitoring and Measurement of Site Infrastructure. Oakland, CA:
Analytics Press. October 23. <http://www.analyticspress.com/scienceofmeasurement.html>
• Taylor, Cody, and Jonathan Koomey. 2008. Estimating energy use and greenhouse gas emissions
of Internet advertising. Working paper for IMC2. February 14. <http://imc2.com/Documents/
CarbonEmissions.pdf>.
• Weber, Christopher, Jonathan G. Koomey, and Scott Matthews. 2010. "The Energy and Climate
Change Impacts of Different Music Delivery Methods." The Journal of Industrial Ecology. vol. 14,
no. 5. October. pp. 754–769. [http://dx.doi.org/10.1111/j.1530-9290.2010.00269.x]
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G.
Koomey
2012